Biology subjects

Welte, A.

Publications and source records attributed to Welte, A..

3 recordsLinked to original sources

bioRxiv2018

Interpreting Diagnostic Histories into HIV Infection Time Estimates: Framework and Online Tool

BackgroundIt is frequently of epidemiological and/or clinical interest to estimate the date of HIV infection or time-since-infection of individuals. Yet, for over 15 years, the only widely-referenced infection dating algorithm that utilises diagnostic testing data to estimate time-since-infection has been the Fiebig staging system. This defines a number of stages of early HIV infection through various standard combinations of contemporaneous discordant diagnostic results, using tests of different sensitivity.\n\nObjectiveTo develop a new, more nuanced infection dating algorithm, we generalised the Fiebig approach to accommodate positive and negative diagnostic results generated on the same or different dates, and arbitrary current or future tests - as long as the test sensitivity is known. For this purpose, test sensitivity is conceptualised as the probability that a specimen will produce a positive result, expressed as a function of time since infection. This can be summarised as a median diagnostic delay parameter, together with a measure of inter-subject variability.\n\nMethodsThe present work outlines the analytical framework for infection date estimation using subject-level diagnostic testing histories, and data on test sensitivity. We introduce a publicly-available online HIV infection dating tool that implements this estimation method, bringing together 1) curatorship of HIV test performance data, and 2) infection date estimation functionality, to calculate plausible intervals within which infection likely became detectable for each individual. The midpoints of these intervals are interpreted as infection time point estimates and referred to as Estimated Dates of Detectable Infection (EDDIs).\n\nResultsIn many settings, including most research studies, detailed diagnostic testing data are routinely recorded, and can provide reasonably precise estimates of the timing of HIV infection. We present a simple logic to the interpretation of diagnostic testing histories into infection time estimates, either as a point estimate (EDDI) or an interval (earliest plausible to latest plausible dates of detectable infection), along with a publicly-accessible online tool that supports wide application of this logic.\n\nConclusionsThis tool, available at https://tools.incidence-estimation.org/idt/, is readily updatable as test technology evolves, given the simple architecture of the system and its nature as an open source project.

epidemiology↗

bioRxiv2018

Population-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africa

IntroductionThere is a notable absence of consensus on how to generate estimates ofpopulation-level incidence. Incidence is a considerably more sensitive and harder to estimate indicator of epidemiological trends than prevalence. We used a novel hybrid method to estimate HIV incidence by age and sex in a rural district of KwaZulu-Natal, South Africa.\n\nMethodsOur novel method uses an optimal weighting of estimates based on an implementation of a particular synthetic cohort approach (interpreting the age/time structure of prevalence, in conjunction with estimates of excess mortality) and biomarkers of recent infection (combining Lag-Avidity, Bio-Rad Avidity and viral load results to define recent infection, and adapting the method for age-specific incidence estimation). Data were obtained from a population-based cross-sectional HIV survey conducted in Mbongolwane and Eshowe health service areas in 2013.\n\nResultsUsing the combined method, we find that age-specific HIV incidence in females rose rapidly during adolescence, from 1.33 cases/100 person-years (95% CI:0.98,1.67) at age 15 to a peak of 5.01/100PY (4.14,5.87) at age 23. In males, incidence was lower, 0.34/100PY (0.00-0.74) at age 15, and rose later, peaking at 3.86/100PY(2.52-5.20) at age 30. Susceptible population-weighted average incidence in females aged 15-29 was estimated at 3.84/100PY (3.36-4.40), in males aged 15-29 at 1.28/100PY(0.68-1.50) and in all individuals aged 15-29 at 2.55/100PY (2.09-2.76). Using the conventional recency biomarker approach, we estimated HIV incidence among females aged 15-29 at 2.99/100PY (1.79-4.36), among males aged 15-29 at 0.87/100PY(0.22-1.60) and among all individuals aged 15-59 at 1.66/100PY (1.13-2.27).\n\nDiscussionHIV incidence was very high in women aged 15-30, peaking in the early 20s. Men had lower incidence, which peaked at age 30. The estimates obtained from the hybrid method are more informative than those produced by conventional analysis of biomarker data, and represents a more optimal use of available data than either the age-continuous biomarker or synthetic cohort methods alone. The method is mainly useful at younger ages, where excess mortality is low and uncertainty in the synthetic cohort estimates is reasonably small.\n\nConclusionApplication of this method to large-scale population-based HIV prevalence surveys is likely to result in improved incidence surveillance over methods currently in wide use. Reasonably accurate and precise age-specific estimates of incidence are important to target better prevention, diagnosis and care strategies.

epidemiology↗

bioRxiv2017

Diagnostic, Infection Timing and Incidence Surveillance Applications of High Dynamic Range Chemiluminescent HIV Immuno-Assay Platforms

BackgroundCustom staging assays, including the Sedia HIV-1 Limiting Antigen Avidity EIA (LAg) and avidity modifications of the Ortho VITROS anti-HIV-1+2 and Abbott ARCHITECT HIV Ag/Ab Combo assays, are used to identify recent infections in clinical settings and for cross-sectional HIV incidence estimation. However, the high dynamic range of chemiluminescent platforms allows differentiating recent and longstanding infection on signal intensity, and this raises the prospect of using unmodified diagnostic assays for infection timing and surveillance applications.\n\nMethodsWe tested a panel of 2,500 well-characterised specimens with estimable duration of HIV infection with the three assays and the unmodified ARCHITECT. Regression models were used to estimate mean durations of recent infection (MDRI), context-specific false-recent rates (FRR) and correlation between signal intensity and LAg measurements. A hypothetical epidemiological scenario was constructed to evaluate utility in surveillance applications.\n\nResultsOver a range of MDRIs (reflecting recency discrimination thresholds), a diluted ARCHITECT-based RITA produced lower FRRs than the VITROS platform (FRR {approx} 0.5% and 1.5% respectively at MDRI of 200 days) and the unmodified diagnostic ARCHITECT produces incidence estimates with comparable precision to LAg (RSE {approx} 17.5% and 15% respectively at MDRI of 200 days). ARCHITECT S/CO measurements were highly correlated with LAg ODn measurements (r = 0.80) and values below 200 are strongly predictive of LAg recency and duration of infection less than one year.\n\nConclusionsLow quantitative measurements from the unmodified ARCHITECT obviate the need for additional recency testing and its use is feasible in clinical staging and incidence surveillance applications.

epidemiology↗